YUCLAW v5.3.0
Validation LabSMH Evidence LensXLK Evidence LensCanada Resources EvidenceForward TrackingSignal ReviewExplorerSectorsGitHubPyPILedgerMethodologyHome

Evidence-First Financial AI

Every signal traces to a real SEC filing.

Agent Research API · MCP · LangChain/LlamaIndex · pip install yuclaw
Disclaimer — Research & education only. Not investment advice. Signal labels are research classifications, not buy/sell recommendations.
Current signals — Forward Tracking Ledger
Current research classifications — not recommendations
TickerSignal label Score Evidence coverage
FXIBULLISH+0.4620
XLKBULLISH+0.4390
MSFTNEUTRAL+0.36495
HPENEUTRAL+0.337100
SMHNEUTRAL+0.3360
BACNEUTRAL+0.32936
PYPLNEUTRAL+0.29796
SPYNEUTRAL+0.2930
GSNEUTRAL+0.28786
WFCNEUTRAL+0.27457
DIANEUTRAL+0.2740
MDYNEUTRAL+0.2650
QQQNEUTRAL+0.2600
IWMNEUTRAL+0.2570
DELLNEUTRAL+0.24592
SLBNEUTRAL+0.24170
KRENEUTRAL+0.2400
XOMNEUTRAL+0.23661
XLFNEUTRAL+0.2350
XBINEUTRAL+0.2340
XLBNEUTRAL+0.2270
UUPNEUTRAL+0.22425
COPNEUTRAL+0.22257
IEFNEUTRAL+0.2190
ARMNEUTRAL+0.21795
SLVNEUTRAL+0.21625
BMYNEUTRAL+0.21658
XLINEUTRAL+0.2140
JPMNEUTRAL+0.21179
IBBNEUTRAL+0.2110
TAILNEUTRAL+0.2000
GLDWATCH+0.19559
TMOWATCH+0.18863
PFEWATCH+0.18874
TLTWATCH+0.1820
EEMWATCH+0.1770
ABTWATCH+0.17166
PSXWATCH+0.16862
AAPLWATCH+0.16887
VIXYWATCH+0.15425
AMZNWATCH+0.15390
VXXWATCH+0.14738
AXPWATCH+0.14476
RKLBWEAKENING-0.14188
AMDWATCH+0.138100
INTCWATCH+0.13582
CWATCH+0.13036
NVDAWATCH+0.12688
MSWATCH+0.11987
XLCWATCH+0.1180
LLYWEAKENING-0.10154
XLEWATCH+0.1010
LUNRWATCH+0.09499
COSTWATCH+0.09266
XLYWATCH+0.0840
JNJWEAKENING-0.08384
CVXWATCH+0.08175
XLVWATCH+0.0790
XLREWATCH+0.0730
METAWATCH+0.07294
XLPWATCH+0.0670
PGWATCH+0.06068
DHRWATCH+0.05968
UNHWEAKENING-0.05438
AMATWATCH+0.05175
XLUWEAKENING-0.0480
KOWEAKENING-0.04786
MRVLWATCH+0.04599
GOOGLWEAKENING-0.04589
WMTWEAKENING-0.04087
MUWATCH+0.02895
LRCXWATCH+0.02875
TSLAWEAKENING-0.02769
MAWEAKENING-0.02787
PEPWATCH+0.01267
MRKWATCH+0.01162
CRCLWEAKENING-0.004100
VWATCH+0.00284
ABBVWATCH+0.00067

Evidence coverage = how much evidence stands under this classification — coverage, not prediction (Evidence Coverage v1, registered protocol). Score = composite research score. It is not an expected return, a probability, a price target, or a recommendation.

data as of 2026-08-04 17:00 UTC · landing page rebuilt 2026-08-05 05:08 UTC
Public signal vocabulary

Labels are research classifications, not buy/sell recommendations:

STRONG_BULLISH · BULLISH · NEUTRAL · WATCH · WEAKENING · NEGATIVE_EVENT · BEARISH_WATCH · RISK_ALERT

There is no SELL or SHORT label. The SDK's _validate_label() is invoked on every signal-bearing return.

How it works

1 · Evidence layer

SEC EDGAR filings (Form 4, 8-K, 10-Q, 10-K, 6-K, 40-F) are extracted with a local Llama 3.1 70B model. A deterministic SourceLock Guard validates every extraction against the source text before any signal sees it.

2 · Composite scoring

Nine components combine into a confidence-weighted composite. C6 event impact carries the highest weight (0.18) — by design, the evidence layer leads.

3 · Time-machine replay

Any signal can be recomputed as of a past date. Point-in-time filtering (available_as_of <= as_of) is leak-audited; reproducible via the yuclaw replay CLI or REST API.

4 · Verified Research Ledger

Each day's published signals have their content hashes committed to a public git repo (yuclaw-trust). Anyone can call yuclaw verify to confirm a signal hasn't been edited since publication.

Full disclaimer & methodology

Open-source equity research where every composite signal traces back to a verifiable SEC filing or deterministic supply-chain cascade. Replayable point-in-time. Tamper-evidenced via a public git-anchored Verified Research Ledger. Research and education only.

Disclaimer — YUCLAW research output. Not investment advice. Past performance does not guarantee future results. Signal labels are research classifications, not buy/sell recommendations. YUCLAW is not a registered investment adviser. Past results — in-sample or forward-tracked — do not predict future performance.
Use YUCLAW in your research
1 · Verify the record

pip install yuclaw then yuclaw replay-lab.
No install: tools/replay_lab.py (stdlib only) against the published bundle.
Exit 0 = every statistic and ledger root reproduced. How to report a replication →

2 · Inspect one evidence trace

One real Suncor 6-K, end to end:
filing → exhibit → extracted prose → event type → grade → C6 posture.
Open the trace → · example evidence memo (Suncor) →

3 · Cite a research lens

Every evidence packet ships a ready citation snippet
(version, data-through, build date, source commit).
Get the citation →

📖 User Guide (PDF) — from pip install to full verification, six pages. · 📖 Guide de l'utilisateur (FR)

Status — proven · not proven · accruing

Rendered from one shared source (v3/web/useful_blocks.py) on every page that shows it, so the copies cannot drift. Statuses are measured, not aspirational.

Proven (verifiable today)
  • ✓ Replay works — one command reproduces every Lab statistic and ledger root from published data
  • ✓ Ledger anchored daily — sha-256 daily roots committed to a public git repository before pages update
  • ✓ Evidence traces to filings — every accepted event carries a source URL, accession number, and verified excerpt
  • ✓ Coverage measured — SEC-filer weight per lens is stated as measured, never rounded up
  • ✓ Snapshots are point-in-time — daily as-of writes, zero retroactive edits (outage window disclosed, not repaired)
  • ✓ Evidence-tier names are never scored — enforced by positive gating and a standing negative check
Not proven
  • ✗ Forward alpha — no spread, IC, or alpha significant at 5% with adequate power
  • ✗ C6 risk-gate sign — rareness confirmed OOS 2026-07-06 (22% fire rate, n=9 held-out); sign confirmation pending (elevated arm n=2; accrual live from 2026-07-16)
  • ✗ Peer-model CAR lead — event-study lead over peer models is not established; live-era sample remains small
Accruing
  • · Forward out-of-sample record — one period per trading day, accruing daily
  • · Matured CAR events — each accepted event matures into the event study after its forward window completes
  • · C6 elevated arm — live Form-4 ingestion since 2026-07-16 restores the insider stream to production inputs
  • · External replications — the replication log accrues as independent runs are reported
For AI agents & researchers

YUCLAW is the open evidence layer underneath AI research tools. Start with llms.txt and the machine-readable evidence_index.json (every page, packet, and protocol with stable URLs and data-through dates). Packets carry derived statistics, event CSVs, engine run JSONs, and citation snippets; yuclaw replay-lab re-computes the published statistics from the public bundle. Derived data only — preserve the disclaimers when quoting; nothing here is advice or a recommendation.

Install + try it
pip install yuclaw
yuclaw demo                         # 3-minute guided "Why AMD?" journey
yuclaw why AMD --as-of 2026-05-20   # bundled offline signal
yuclaw verify AMD --date 2026-05-20 # check the ledger record
# all tickers/dates: connect the local backend — see README

SDK + REST API + MCP server documented at github.com/YuClawLab/yuclaw-brain. REST API terms at /API_TERMS.md.

YUCLAW v5.3.0 · YuClawLab · Full Disclaimer · 🚀 5-minute tour · 🤖 For AI builders · 📐 EvidenceBench · 📖 User Guide (PDF) · 📖 Guide de l'utilisateur (FR) · Methodology · Replication · Today's Evidence Changes · YUCLAW's Lane · Weekly Note · Apache-2.0 Licensed